Strategic Data-planning Methodologies
Title | Strategic Data-planning Methodologies PDF eBook |
Author | James Martin |
Publisher | Prentice Hall |
Pages | 260 |
Release | 1982 |
Genre | Business & Economics |
ISBN |
Textbook on methodology for the systems design of management information systems and information systems - stresses the need for top management involvement in decision making relating to the computerization of business enterprises, and includes a glossary of terms. Bibliography pp. 228 and 229 and diagrams.
Strategic Data Planning
Title | Strategic Data Planning PDF eBook |
Author | Dale L. Goodhue |
Publisher | |
Pages | 42 |
Release | 2015-08-05 |
Genre | Business & Economics |
ISBN | 9781332283248 |
Excerpt from Strategic Data Planning: Lessons From the Field Many large organizations today are finding that even if they can access data from multiple functions, the lack of logical data integration (common data definitions and codes) across information systems makes it difficult or impossible to answer cross-functional or cross-divisional questions. This reduces their ability to take advantage of potential opportunities or respond to business problems. Strategic Data Planning is one methodology which can address such problems, within the general umbrella of information engineering. Resting on the assumption that a relatively stable group of data entities lies at the center of an organization's information processing needs, SDP is a formalized, top-down, data-centered planning approach that builds a model of the enterprise, its functions, and its underlying data as a basis for identifying and implementing an integrated set of information systems. In spite of strong conceptual arguments for the value of the SDP approach and its use in many organizations, empirical researchers have failed to find clear-cut evidence of its general success. This raises the question of whether the approach is universally appropriate. If success is somewhat problematic, are there lessons that can be drawn from actual organizational experience? The purpose of this paper is to report the results of a series of case studies of SDP efforts, to offer insights on the conditions under which SDP is most effective, and to propose directions for future research. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Strategic Data Planning: Lessons from the Field
Title | Strategic Data Planning: Lessons from the Field PDF eBook |
Author | Dale L. Goodhue |
Publisher | Sagwan Press |
Pages | 46 |
Release | 2015-08-25 |
Genre | Business & Economics |
ISBN | 9781340308605 |
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Data Strategy
Title | Data Strategy PDF eBook |
Author | Bernard Marr |
Publisher | Kogan Page Publishers |
Pages | 201 |
Release | 2017-04-03 |
Genre | Business & Economics |
ISBN | 0749479868 |
BRONZE RUNNER UP: Axiom Awards 2018 - Business Technology Category Less than 0.5 per cent of all data is currently analyzed and used. However, business leaders and managers cannot afford to be unconcerned or sceptical about data. Data is revolutionizing the way we work and it is the companies that view data as a strategic asset that will survive and thrive. Data Strategy is a must-have guide to creating a robust data strategy. Explaining how to identify your strategic data needs, what methods to use to collect the data and, most importantly, how to translate your data into organizational insights for improved business decision-making and performance, this is essential reading for anyone aiming to leverage the value of their business data and gain competitive advantage. Packed with case studies and real-world examples, advice on how to build data competencies in an organization and crucial coverage of how to ensure your data doesn't become a liability, Data Strategy will equip any organization with the tools and strategies it needs to profit from Big Data, analytics and the Internet of Things (IoT).
Business Intelligence Strategy and Big Data Analytics
Title | Business Intelligence Strategy and Big Data Analytics PDF eBook |
Author | Steve Williams |
Publisher | Morgan Kaufmann |
Pages | 241 |
Release | 2016-04-08 |
Genre | Computers |
ISBN | 0128094893 |
Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like "big data and "big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans
Strategic Data Planning
Title | Strategic Data Planning PDF eBook |
Author | |
Publisher | |
Pages | 33 |
Release | 1990 |
Genre | Industrial management |
ISBN |
Modern Data Strategy
Title | Modern Data Strategy PDF eBook |
Author | Mike Fleckenstein |
Publisher | Springer |
Pages | 269 |
Release | 2018-02-12 |
Genre | Computers |
ISBN | 3319689932 |
This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.